Split-Plot Optimal Model Selection Screen

Search: Best or Coordinate Exchange or Point Exchange

Optimality: Only D-optimal designs are available at this time. Other optimality criterion will be added in the future.

Blocks: allows the design to be separated into blocks. Adding blocks will add groups and runs to your design to provide additional degrees of freedom to estimate the block effects while allowing useful analysis for the model coefficients.

Edit model: The software will default to a certain type of model, depending on the type of optimal design being created. You may change or customize the model by clicking on the Edit Model button. Adding or subtracting specific terms in a model will alter both the number of runs and specifically which runs are chosen. For more information use the help button on the Edit model button.

Variance ratio: The ratio of the whole plot variance to the subplot variance. A value of 1 is a balanced starting point that will work for most cases.


Required groups is the minimum number of groups to estimate the coefficients for the hard-to-change terms in the designed for model specified under the Edit model button.

Additional groups are added to the experiment to provide degrees of freedom to test the hard-to-change model terms ANOVA. Manually adding more groups will increase the number times the hard-to-change factors must be reset during the experiment. This can be done to balance groups sizes, and is often done to provide a more powerful test for the hard-to-change model.

Center point groups can be added when there are numeric factors to ensure coverage of the space. Replicates of the center point groups provide an estimate of pure error.

Center point group size sets the size of the center point groups.

Total groups is the number of groups that will be in the final design.


Required model points is the minimum number of runs to estimate the coefficients of the terms in the designed for model specified under the Edit model button.

Additional model points are extra runs added to the experiment to improve precision estimates or coverage of the factor space.

Lack-of-fit points provide extra points to fill the factor space. The extra information provided by these points can test the fit of the model.

Replicate points of the above points are chosen to support the optimality.

Additional center points are added as requested.

Total runs is the number of runs that will be in the final design.

Edit Candidate Points: Click this button if want to limit the type of points the design can consider by specifying a custom built candidate set.

Options: The more random starts and loops that are allowed the better the design will meet the chosen optimality criterion. For more details use the help button found on the Options dialog.